Research On Optimization Of Wireless Sensor Networks Based On Improved Ant Colony Algorithm

The Wireless Sensor Network(WSN)is composed of many nodes with computing power and communication function,which can detect special events in specific scenarios.However,the nodes in WSN are powered by their own micro dry cells,which are limited and difficult to charge,and unreasonable energy loss will cause premature death of the nodes.Therefore,how to establish a dynamic routing model that can reduce node energy consumption and select the optimal path is one of the key points to improve WSN performance.Ant colony algorithm is an intelligent multi-agent random search algorithm,the adaptive makes it less disturbed by the external environment,and is often used in WSN routing selection.However,the basic ant colony algorithm selects the optimal path according to the pheromone concentration of the path,and fails to take full account of the factors such as distance,energy,angle and direction,which leads to limited performance improvement of the WSN.In view of the above problems,this paper first studies the impact of parameter values on the selection of optimal path in ant colony algorithm,and proposes an effective way to obtain the optimal parameter range.Taking the Oliver30 TSP model as an example,through several experiments to analyze the different parameters on the performance of the algorithm,thus obtaining the optimal performance under the parameter values,which provides a certain reference value for the parameter selection in the following chapters.Secondly,aiming at the problem of long data transmission path,uneven energy consumption and shorter network lifetime in WSN plane routing protocol,an ant colony optimization routing algorithm based on energy,location information and search direction is proposed.Throughout the search process,the paper considers factors such as energy,transmission distance,transmission angle,search range and the size of ant colony,and introduce path metrics to improve pheromone updating process.The simulation results show that the improved algorithm can effectively reduce the energy consumption of data transmission,balance the energy consumption of nodes and improve the network performance in the application of plane routing.Finally,aiming at the problem of unequal clustering protocol in WSN hierarchical routing,combined with the above ant colony optimization algorithm,an improved unequal clustering algorithm based on ant colony optimization and broadcast timing is proposed.The redundant judgment system is used to confirm the redundant network area,sleep low energy nodes in the area to reduce network energy consumption.The factors such as density,energy consumption anddistance are pushed into the campaign radius formula to solve the hot zone problems.The broadcast timing mechanism is adopted to replace the negotiation mechanism to reduce the energy consumed in the cluster head election.Cluster routing uses ant colony algorithm to find the best route,and reduce the energy required for data transfer.Finally,the rotation mechanism is optimized to avoid excessive energy consumption because of frequent elections.Simulation results verify that the improved algorithm can effectively balance node energy and prolong the lifetime of WSN.